We have continued our investigations of the mathematical basis for the use of light in medical diagnosis and therapy. In particular, we have focused on deriving an inverse algorithm to infer the optical properties of abnormal tissue embedded in an optically turbid background which, to first order, can be taken as optically homogeneous. We have accounted for the fact that the optical properties of the abnormal region may differ only slightly from those of the surrounding normal tissue. The derived algorithm is based on a photon random walk model that uses different time-dependent point spread functions to calculate the diffusive and absorptive contrasts obtained from time-of-flight measurements. Because the diffusive and absorptive contrast functions have differing time-dependent behaviors, one can discriminate between absorbing and scattering contributions to the total detected contrast. In addition to providing information about the optical cross-sections of the unusual region, calculations based on the algorithm also yield a measure of the size of the inclusion. Working in collaboration with investigators from the Department of Medical Physics of University College, London, we have examined tissue-like phantoms and have demonstrated an ability to determine optical parameters to an accuracy of 10-15%. Although in its present version the algorithm cannot reconstruct the detailed shape of the target, we obtained equivalent cubic volumes whose average dimensions differ from the known dimensions of the targets by less than 20%. Related studies have been carried out to develop an image reconstruction algorithm to quantify concentrations of fluorophores located at discrete sites below the surface of an optically turbid medium. These are being used in a collaborative project aimed at developing a non-destructive optical biopsy technique for the quantification of lymphocyte infiltration of the minor salivary glands, undertaken in order to diagnose and follow the progression and response to therapy of the autoimmune disease known as Sjogren's syndrome.